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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Overview of collaborative research between UNICAMP in Brazil and Fermilab in cryogenics

The Long-Baseline Neutrino Facility (LBNF) situated at the Sanford Underground Research Facility (SURF) in Lead, South Dakota, serves as the host for the Deep Underground Neutrino Experiment (DUNE), employing cryostats with nearly 70,000 metric tons of high purity liquid argon (LAr). The integrity of LAr quality is pivotal in determining the electron lifetime within DUNE, directly impacting its signal-to-noise ratio. Specifically, Far Detector 1 (FD-1) in cryostat 1 requires an electron lifetime over 3 ms within its 3.5 m drift, corresponding to less than 100 parts-per-trillion (ppt) Oxygen equivalent contamination. Far Detector 2 (FD-2) in cryostat 2 demands over 6 ms electron lifetime within its 6.0 m drift, corresponding to less than 50 ppt Oxygen equivalent contamination. Nitrogen (N$_2$) absorption of LAr scintillation light, known as quenching, necessitates N$_2$ contamination in LAr to remain below 1 ppm to minimize photon loss and enhance energy reconstruction. Studies indicate that at 1 ppm N$_2$, approximately 20% of scintillation light is lost, highlighting the importance of minimizing N$_2$ contamination.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Fitness-for-Service Analysis of Reactor Components under Flexible Load-Following Operating Conditions

Conventional power-generation plants, including nuclear plants, have been traditionally designed to provide a steady baseload energy capacity, optimizing output efficiency while minimizing variable costs. However, the growing adoption of large-scale renewable energy-generation systems, which rely on intermittent sources such as solar and wind, has introduced more variability into the energy supply in interconnected electricity grids. As a result, the next generation of power plants needs to operate in what is known as the load-following mode, requiring flexible adjustments in electricity production to align with the energy demand on the grid. This transition from the steady baseload operation to load-following operating conditions can significantly increase the number of times various plant components are exposed to transient stresses. This increased thermo-mechanical cycling can lead to accelerated material degradation, thereby elevating the risk of premature failure of a component. It becomes imperative to conduct a comprehensive analysis of fatigue, creep-fatigue, and stress corrosion cracking life, to assess the resilience of the various engineering components under these flexible load-following operating conditions. This study aims to develop a comprehensive numerical model of a light-water reactor pressure vessel (RPV) to investigate its degradation under various operating scenarios. This coupled thermo-mechanical finite element analysis evaluated the stress response of the RPV caused by considering fluctuations in thermal and mechanical loads caused by the varying pressure and temperature occurring during the load-following operation. Critical locations on the RPV are subsequently identified based on the stress response. The stress intensity factors for the postulated flaws at those locations are then calculated, followed by an evaluation of the reactor's life in accordance with the ASME Boiler and Pressure Vessel Code Section XI. This comprehensive life assessment covers a number of transients expected during the flexible load-following operation, providing invaluable insights into the RPV's structural integrity. Moreover, the development methodology can be adapted to other reactor components, as well as components of conventional power stations that are affected by varying operating conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Multi-Modal Energy Analysis for Freight

This project addresses the impact of emerging technologies on inter-city freight energy demand, shipping time, and cost. Technologies addressed include electrified long-haul trucks, connectivity and efficient operations, and platooning. The research questions are addressed using national level analysis, a multi-modal inter-city freight energy model, and development of a Freight Mobility Energy Productivity (F-MEP) metric. This project improves on prior analysis and modeling by increasing the geographic and temporal resolution of freight flows. The inter-city freight energy model uses a bi-level optimization approach to minimize total network cost (lower level) and energy (upper level). Two new F-MEP frameworks are presented, one for intra-city freight mobility and one for inter-city freight mobility.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Designing Monte Carlo Simulation and an Optimal Machine Learning to Optimize and Model Space Missions

This paper investigates applying artificial intelligence (AI) algorithms to attitude control system of satellites to optimally tune the controller using high performance computing. This methodology is applied to the Virtual Telescope for X-ray Observation mission, which is a precise formation of two separate spacecraft observing multiple objects in the space in the X-ray domain. The mission is divided into phases based on the instrumentation and the mission goal. To reach an stable precise formation robust to stochastic slew and slew rate (i.e., Euler angles and angular velocities) in a minimal constrained time T , consumed energy of the attitude control system, denoted as E, and root-mean-square state error of attitude control system, denoted as e, are minimized. Monte-Carlo simulation is used for the sensitivity analysis of optimization and designing a controller. Deep neural networks (DNN), Gaussian processes (GP), and support vector regression (SVR) learn this optimization as a surrogate model, while their hyperparameters are optimized in a novel approach. THETA supercomputer at Argonne Leadership Computing Facility (ALCF) is used for optimizing the hyperparameters of DNN. The surrogate model meets the requirements of the mission, and it shows a better performance over the optimization and Monte-Carlo. The optimal DNN can satisfy the mission requirements e and T while reducing E for 90% compared to the other given methods.

42 ENGINEERING↗
DOE OSTI2021

Direct Air Capture of CO2 (DAC) [Tech Snapshot]

Researchers at Los Alamos have extensive capabilities in design, testing and optimization of: (1) new capture materials based on membrane separation, amine and other solvent and sorbent separation, and porous materials; (2) biological capture methods, particularly algae and plants; (3) full-scale systems using science-based virtual learning; and (4) system performance under specific meteorological conditions, impacts of CO2 capture via atmospheric data and simulations, and availability of energy and storage capacity. The goal for Los Alamos is advancing our physical technologies and engineered systems approaches from the development phase to a minimal viable product in the energy sector for commercial purposes. Los Alamos is seeking strategic commercialization partners to work with us in advancing these capabilities and technologies for commercial viability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Using hydrogen and ammonia for renewable energy storage: A geographically comprehensive techno-economic study

Hydrogen and, more recently, ammonia have received worldwide attention as energy storage media. In this work we investigate the economics of using each of these chemicals as well as the two in combination for islanded renewable energy supply systems in 15 American cities representing different climate regions throughout the country. We use an optimal combined capacity planning and scheduling model which minimizes the levelized cost of energy (LCOE) by determining optimal unit selection and size along with unit commitments, production rates, and storage inventories for each period of system operation. These periods are aggregated from full year hourly resolution data via a consecutive temporal clustering algorithm. Ammonia is generally more economical than hydrogen as a single method of energy storage. Additionally, systems which use both hydrogen and ammonia outperform those which use only one storage option and have LCOE between $\$ 0.17$/kWh and $\$ 0.28$/kWh, including full investment in renewable generation infrastructure.

25 ENERGY STORAGE↗
DOE OSTI2022

Local magnetic moments due to loop currents in metals

We present Hartree-Fock calculations on a simple model to obtain the conditions of formation of local magnetic moments due to loop currents $L$ $o$ and spin-loop currents $L$ $s$ and compare them to the conditions of formation of local spin moments $M$ which were given long ago in a similar approximation by Anderson. A model with three degenerate orbitals sitting on an equilateral triangle, with on-site and nearest-neighbor repulsions $U$ and $V$, respectively, and intersite kinetic energy, hybridizing with conduction electrons with a parameter $Δ$ is investigated. $L$ $o$ and $L$ $s$ are promoted by large $V$/$Δ$ and their magnitude is relatively unaffected by $U$/$Δ$. Spin-magnetic moments $M$ promoted by large $U$/$Δ$ on the other hand are adversely affected by $V$/$Δ$. In this model, $L$ $o$ for $V$ multiplied by the number of neighbors is approximately the same as the $M$ promoted by $U$ in Anderson’s local model for $M$. $L$ $o$ and $L$ $s$ are degenerate if exchange interactions and Hund’s rule are neglected but $L$ $o$ is favored when they are included. Many of the qualitative results are visible in an expression for the Hartree-Fock ground state energy derived as a function of small $L$ $o$ , $L$ $s$ , and $M$. Numerical minimization of the Hartree-Fock energy is presented for larger values. Additionally, we also briefly discuss the connection and differences of the interaction-generated orbital currents and spin currents discussed here and generalized to a lattice with the topological states in metals and semiconductors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Initial Fermi orbital descriptors for FLOSIC calculations: The quick-FOD method

Fermi orbital descriptors (FODs) play a key role in Fermi-Löwdin orbital self-interaction correction (FLOSIC) calculations used to remove self-interaction from approximate density functionals. Optimal FODs are obtained by minimizing the self-interaction-corrected total energy, and, in this process, identifying initial sets of FODs becomes crucial. Here we propose, implement and test a novel method for automatically initializing FODs, quick-FOD, based on the minimization of an empirical energy expression that involves a Coulomb-like FOD-electron density attraction, an FOD-FOD short-range repulsion, and an exchange-like FOD-density repulsion. Quick-FOD successfully reproduces FOD arrangements in qualitatively good agreement with Lewis theory and with full-fledged FLOSIC calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Optimal Sizing of an Electric Vehicle Charging Station with Integration of PV and Energy Storage

This paper proposes an optimization model for the optimal configuration of an grid-connected electric vehicle (EV) extreme fast charging station considering integration of photovoltaic (PV) and energy storage. The proposed model minimizes the annualized net cost (i.e., maximizes the annualized net profit) of the extreme fast charging station, including investment and maintenance cost of charging ports, PV and energy storage, net cost of purchasing energy from utility and selling energy to EV customers, degradation cost of energy storage and demand charge. The decision variables are number of charging ports, capacity of invested PV and the power and energy ratings of invested energy storage. The Erlang-loss system is adopted to model the EV mobility. Results of numerical simulations indicate that investment of PV and energy storage could increase the annualized profit of the extreme fast charging station. In addition, the impacts of various parameters on the optimal solution are investigated by sensitivity analysis.

Liu, Guodong↗
DOE OSTI2023

Liquid Air Combined Cycle TM for Power and Storage

Liquid Air Combined Cycle (LACC) is a hybrid liquid air energy storage (LAES) system combining energy storage with a combustion turbine to enable large-scale, long-duration energy storage (LDES) while reducing fuel intensity compared to the current state-of-the-art. The LACC technical approach employs proven equipment (cryogenic refrigeration, storage, tanks, pumps, gas turbines, exhaust heat recovery equipment, and turbines) to limit technical risk to a novel organic Rankine cycle (ORC), which was evaluated during this project and found to be feasible. Moreover, LACC storage is safe and relatively compact, to facilitate siting close to loads and within metropolitan regions. The air storage medium is freely available and eliminates supply chain constraints. LACC uses cryogenic air as a storage medium and a gas turbine as the source of heat to drive the discharge process. LACC is distinguished from other LAES technologies by several factors. The charge and discharge processes are decoupled so that cryogenic liquid air is the only storage medium. Other systems also store the higher temperature thermal energy from the liquefaction process in an additional medium. Subsequently, LACC focuses on maximization of the discharge energy and power. LACC also permits the use of commercially available cryogenic refrigeration and storage technologies to increase competition. This project identified product requirements to support market entry and commercialization of the LACC in modular units of approximately 117 MW, each drawing liquid air from customary cryogenic storage tanks capable of storing 75 GWh of dispatchable energy, more than pumped storage hydro or compressed air energy storage technologies. An economic analysis identified the specific liquid air consumption (quantity of liquid air per unit of discharge energy) as a critical parameter. Minimizing the air consumption reduces the specific capital cost ($\$ $/kW) for charging and discharging equipment by reducing the size of piping and turbomachinery. Likewise, the specific cost of energy capacity ($\$ $/kWh) is reduced by increasing the energy deliverable from a given size tank. The cycle was analyzed to identify the optimal equipment selection and operating conditions, which in turn were combined with quotes and cost estimates to calculate the cost of energy from an LACC system. A substantial effort was focused on the ORC, which draws low-temperature heat from the gas turbine exhaust and condenses at low temperature using the cryogenic liquid air as a heat sink. Alternative turbomachinery arrangements were evaluated for feasibility and cost. A technology maturation plan lays out a low-risk approach to development of the novel ORC components and demonstration of LACC technology at pilot scale.

25 ENERGY STORAGE↗
DOE OSTI2020

Controlled workplace charging of electric vehicles: The impact of rate schedules on transformer aging

To accelerate adoption of non-residential charging for electric vehicles, sites must maximize utilization of existing electrical infrastructure. In this study we model electric vehicle charging at a workplace using real charging data and evaluate the lifetime of the site’s transformer as the number of charging stations is incrementally increased. We implement and compare a range of control schemes for workplace charging including minimizing the peak load, capping the total load, minimizing bills under different rate structures with time-of-use energy costs and demand charges, and directly minimizing the transformer’s aging. These are compared by the number of vehicles they allow the transformer to support, the transformer’s health, and the operator’s electricity bill. We draw a connection between minimizing the peak load and improving the transformer’s health. We observe that minimizing the electricity bill is the best scheme by both criteria when the bill includes a demand charge; in our experiment it allowed the infrastructure to support over 67% more cars than under uncontrolled charging. To protect the transformer we recommend that demand charges or capacity management be applied to parking lots of charging electric vehicles with high infrastructure utilization, and operators schedule charging to minimize their electricity bills.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Inputs and Outputs for paper "The DESC stellarator code suite. Part 1. Quick and accurate equilibria computations"

Contains the DESC and VMEC input and output files used in the paper, as well as the plotting scripts used to create the figures in the paper (Current with the arXiv Mar 31 2022 version, https://arxiv.org/abs/2203.17173v1): 3D equilibrium codes are vital for stellarator design and operation, and high-accuracy equilibria are also necessary for stability studies. This paper details comparisons of two 3D equilibrium codes, VMEC, which uses a steepest-descent algorithm to reach a minimum-energy plasma state, and DESC, which minimizes the MHD force error in real space directly. Accuracy as measured by final plasma energy and satisfaction of MHD force balance, as well as other metrics, will be presented for each code, along with the computation time. It is shown that DESC is able to achieve more accurate solutions, especially near-axis. DESC's global Fourier-Zernike basis also yields the solution everywhere in the plasma volume, not just on discrete flux surfaces. Further, DESC can compute the same accuracy solution as VMEC in an order of magnitude less time.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Optimal Operation of PV Sources in DC Grids for Improving Technical, Economical, and Environmental Conditions by Using Vortex Search Algorithm and a Matrix Hourly Power Flow

This document presents a master–slave methodology for solving the problem of optimal operation of photovoltaic (PV) distributed generators (DGs) in direct current (DC) networks. This problem was modeled using a nonlinear programming model (NLP) that considers the minimization of three different objective functions in a daily operation of the system. The first one corresponds to the minimization of the total operational cost of the system, including the energy purchasing cost to the conventional generators and maintenance costs of the PV sources; the second objective function corresponds to the reduction of the energy losses associated with the transport of energy in the network, and the third objective function is related to the minimization of the total emissions of CO2 by the conventional generators installed on the DC grid. The minimization of these objective functions is achieved by using a master–slave optimization approach through the application of the Vortex Search algorithm combined with a matrix hourly power flow. To evaluate the effectiveness and robustness of the proposed approach, two test scenarios were used, which correspond to a grid-connected and a standalone network located in two different regions of Colombia. The grid-connected system emulates the behavior of the solar resource and power demand of the city of Medellín-Antioquia, and the standalone network corresponds to an adaptation of the generation and demand curves for the municipality of Capurganá-Choco. A numerical comparison was performed with four optimization methodologies reported in the literature: particle swarm optimization, multiverse optimizer, crow search algorithm, and salp swarm algorithm. The results obtained demonstrate that the proposed optimization approach achieved excellent solutions in terms of response quality, repeatability, and processing times.

14 SOLAR ENERGY↗
DOE OSTI2024

Analysis of the Aeroelastic Dynamics of Lightweight Flexible Variations of the SNL-NRT Turbine

Current trends show that wind turbines are growing in size to meet a rising demand for renewable energy generation, and their upscaled rotors have inherently become more flexible to maintain a proportionally lighter design. This is because larger rotors must be less massive relative to their diameter to minimize the levelized cost of energy (LCOE), which means that blades that are notably less stiff are produced as a result. These structural changes to blades are often reflected in their compromised aeroelastic stability and amplified deformation during operation, which has the potential to decrease the blade’s expected lifetime and the performance of the machine overall. Variations in blade flexibility are also known to influence vortex-wake structures downstream of the turbine, causing patterns of velocity deficit to evolve in ways that affect the performance of other turbines in the farm. This research explores how the increased flexibility of modern utility-scale wind turbine blades influences rotor aeroelastic behavior and interactions with farm flow. High-fidelity simulations of Sandia National Laboratories’ (SNL) National Rotor Testbed (NRT) wind turbine are presented. Flexible variations of the NRT baseline blade are simulated in a variety of realistic operational conditions typically expected at the SNL’s SWiFT facility in Lubbock, Texas. Solutions are then compared to investigate how specific changes to the structural properties of the NRT baseline blade’s design and construction can influence its aeroelastic response at the rotor and the evolution of the turbine’s wake.

Farrell, Alayna (ORCID:000000023555720X)↗
DOE OSTI2021

Wind and Wildlife Co-Exist With Help From ECO Wind

Sustainable deployment of wind energy requires a balance of conservation, energy, and economic goals. The Enabling Coexistence Options for Wind Energy and Wildlife (ECO Wind) program at the U.S. Department of Energy National Renewable Energy Laboratory (NREL) supports efforts to reduce wildlife impacts at land-based and offshore wind energy facilities with monitoring and minimization technology solutions.

50 EE - Wind and Water Power Program - Water (EE-4↗
DOE OSTI2021

HVAC System Performance for Energy Codes (Technical Brief)

The prescriptive path is likely the most widely used approach for commercial code compliance in the United States. Though easy to implement, the prescriptive approach does not discriminate between high-performing and poorly performing heating, ventilation, air conditioning (HVAC) system configurations that are both minimally compliant. To meet aggressive energy and carbon reduction goals, energy codes will need to transition from prescriptive to performance-based approaches, a transition that is riddled with several challenges. HVAC System Performance is a discipline performance path and provides a simpler solution to HVAC system evaluation compared to whole building performance, while keeping tradeoffs limited to specific building systems. The Total System Performance Ratio (TSPR) is a metric for evaluation of overall system efficiency instead of individual component efficiency, a solution that could also eventually facilitate the transition to a 100% performance-based code structure. TSPR is a ratio that compares the annual heating and cooling load of a building to the annual energy consumed by the building’s HVAC system. A web-based calculation tool has been developed for determining a building’s TSPR. Already incorporated into the 2018 Washington State Energy Code, this approach has also been evaluated by the ASHRAE Standard 90.1 Project Committee and has the potential to provide a comprehensive performance-based approach for HVAC system evaluation and analysis

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Evolution of the electronic structure in Ta 2 NiSe 5 across the structural transition revealed by resonant inelastic x-ray scattering

We utilized high-energy-resolution resonant inelastic X-ray scattering (RIXS) at both the Ta and Ni L 3 -edges to map out element-specific particle-hole excitations in Ta 2 NiSe 5 across the phase transition. Our results reveal a momentum dependent gap-like feature in the low energy spectrum, which agrees well with the band gap in element-specific joint density of states calculations based on ab initio estimates of the electronic structure in both the low temperature monoclinic and the high temperature orthorhombic structure. Below T c , the RIXS energy-momentum map shows a minimal gap at the Brillouin zone center (~0.16 eV), conforming that Ta 2 NiSe 5 possesses a direct band gap in its low temperature ground state. However, inside the gap, no signature of anticipated collective modes with an energy scale comparable to the gap size can be identified. Upon increasing the temperature to above T c , whereas the gap at the zone center closes, the RIXS map at finite momenta still possesses the gross features of the low temperature map, suggesting a substantial mixing between the Ta and Ni orbits in the conduction and valence bands, which does not change substantially across the phase transition. Our experimental observations and comparison to the theoretical calculations lend further support that the phase transition and the corresponding gap opening in Ta 2 NiSe 5 is largely structural by nature with possible minor contribution from the putative exciton condensate.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗